Data Engineer (Lead-Staff Level)

Our client?

Our client is a large-scale technology organisation with a strong focus on engineering, data, and AI. They are continuing to invest in AI/ML platform capabilities that enable teams to build, operate, and scale machine learning and intelligent applications more effectively.

About the Role

They are hiring a Lead/Staff Data Engineer to join a high-impact team sitting at the intersection of data engineering, business analytics, ML engineering, and backend engineering. The team builds the pipelines, platforms, and tools that let the Data Science and Performance Marketing teams run experiments in production at scale.

This is a hands-on technical leadership role for an experienced engineer with a strong data-driven mindset. You will work across structured and unstructured data at massive scale, on systems where quality, accuracy, speed, and efficiency are critical.

You will take end-to-end ownership of building the systems that let experiments launch in production at pace.

*Relocation sponsorship is provided

Responsibilities

• Provide technical leadership in improving the scalability, quality, accuracy, speed, and efficiency of existing data and ML processes
• Analyze data to support better business decision-making
• Design, build, and test tools, libraries, pipelines, and platforms that help Data Science and Business teams launch experiments in production
• Partner with experienced engineers and product owners to identify and build tools that automate large-scale data management, analysis, and ML tasks
• Take end-to-end ownership of systems that enable rapid experiment launches in production

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field
• 6+ years of software engineering experience, including 4+ years specifically in data/ML engineering
• Expert in designing, writing, and maintaining data pipelines and systems while ensuring data quality
• Expert-level SQL, Python3, and a JVM-based language (Java or Scala)
• Expert in software design/design patterns/best practices, and both functional and object-oriented programming
• Comfortable across a modern data/ML stack: Python3, Scala Spark, Hadoop, SQL, S3, and similar
• Familiar with general machine learning concepts and common models (e.g. regularization, tree models)
• Familiar with core statistical analysis concepts (e.g. p-value, z-score)
• Strong analytical problem-solving capabilities and a data-driven engineering mindset

Nice to Have

• Good understanding of Hadoop ecosystems and Big Data architecture
• Experience with Scala/Scala Spark development
• Comfort working in an agile, test-driven environment
• Linux systems administration skills

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